Protocol for a systematic review of the predictive and translational validity of simulation-based training in neurosurgery
9 affiliations
- 1RCSI SIM Centre for Simulation Education and Research, RCSI University of Medicine and Health Sciences
- 2Department of Surgical Affairs, RCSI University of Medicine and Health Sciences
- 3Department of Neurosurgery, Temple Street Hospital
- 4School of Medicine, RCSI University of Medicine and Health Sciences
- 5Department of Plastic & Reconstructive Surgery, Cork University Hospital
- 6Library, RCSI University of Medicine and Health Sciences
- 7Department of Neurosurgery, Beaumont Hospital
- 8Fondazione IRCCS Istituto Neurologico “Carlo Besta”
- 9Faculty of Life Sciences & Medicine, King’s College London
Abstract
Background Simulation-based training (SBT) has become integral in neurosurgical education, aiming to enhance technical skills and patient safety. While advanced modalities, such as virtual reality (VR), augmented reality (AR), three-dimensional (3D) printing, and artificial intelligence (AI)-enhanced platforms, are increasingly adopted, evidence linking simulator performance to operative competence and patient or system-level outcomes remains limited. This protocol describes a systematic review evaluating the predictive and translational validity of neurosurgical SBT. Methods Eligible studies will include neurosurgical trainees and practitioners undergoing SBT or assessment. A comprehensive search strategy, developed with an information specialist, will interrogate MEDLINE, Embase, Scopus, Web of Science, CINAHL, and the Cochrane Library. Inclusion criteria will focus on studies reporting outcomes related to operative competence, technical performance, or patient outcomes; studies assessing only learner satisfaction or knowledge without performance metrics will be excluded. Three reviewers will independently screen studies, extract data using a structured tool, and assess study quality using Messick’s validity framework, the Beckman scale, and the Modified Translational Outcomes of Simulation-Based Mastery Learning (TO-SBML) framework to inform an integrated, structured narrative synthesis. Discussion This review will provide an evidence-informed synthesis of the predictive and translational validity of neurosurgical SBT, including AI-enhanced platforms, and identify methodological gaps that limit translation from simulator performance to operative, patient, and system-level outcomes. The findings are expected to inform curriculum design, competency-based assessment, credentialling, and decisions regarding the implementation and resourcing of SBT, while helping prioritise future research in areas where robust translational evidence remains limited. Systematic review registration PROSPERO registration: CRD420251131906.
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BibTeX
@article{roche2026protocol,
title = {{Protocol for a systematic review of the predictive and translational validity of simulation-based training in neurosurgery}},
author = {Adam F. Roche and Andrea J. Doyle and Dara O. Kavanagh and Darach Crimmins and Deborah Shinyanbola and Lena Dablouk and Killian Walsh and Gulam Zilani and Vincent Healy and Alessandro Perin and Abdullatif Aydin and Claire M. Condron},
journal = {Systematic Reviews},
year = {2026},
month = jul,
doi = {10.1186/s13643-026-03274-y},
url = {https://doi.org/10.1186/s13643-026-03274-y},
note = {CC BY},
}
RIS
TY - JOUR
TI - Protocol for a systematic review of the predictive and translational validity of simulation-based training in neurosurgery
AU - Adam F. Roche
AU - Andrea J. Doyle
AU - Dara O. Kavanagh
AU - Darach Crimmins
AU - Deborah Shinyanbola
AU - Lena Dablouk
AU - Killian Walsh
AU - Gulam Zilani
AU - Vincent Healy
AU - Alessandro Perin
AU - Abdullatif Aydin
AU - Claire M. Condron
PY - 2026
DA - 2026/07/01
JO - Systematic Reviews
DO - 10.1186/s13643-026-03274-y
UR - https://doi.org/10.1186/s13643-026-03274-y
AB - Background Simulation-based training (SBT) has become integral in neurosurgical education, aiming to enhance technical skills and patient safety. While advanced modalities, such as virtual reality (VR), augmented reality (AR), three-dimensional (3D) printing, and artificial intelligence (AI)-enhanced platforms, are increasingly adopted, evidence linking simulator performance to operative competence and patient or system-level outcomes remains limited. This protocol describes a systematic review evaluating the predictive and translational validity of neurosurgical SBT. Methods Eligible studies will include neurosurgical trainees and practitioners undergoing SBT or assessment. A comprehensive search strategy, developed with an information specialist, will interrogate MEDLINE, Embase, Scopus, Web of Science, CINAHL, and the Cochrane Library. Inclusion criteria will focus on studies reporting outcomes related to operative competence, technical performance, or patient outcomes; studies assessing only learner satisfaction or knowledge without performance metrics will be excluded. Three reviewers will independently screen studies, extract data using a structured tool, and assess study quality using Messick’s validity framework, the Beckman scale, and the Modified Translational Outcomes of Simulation-Based Mastery Learning (TO-SBML) framework to inform an integrated, structured narrative synthesis. Discussion This review will provide an evidence-informed synthesis of the predictive and translational validity of neurosurgical SBT, including AI-enhanced platforms, and identify methodological gaps that limit translation from simulator performance to operative, patient, and system-level outcomes. The findings are expected to inform curriculum design, competency-based assessment, credentialling, and decisions regarding the implementation and resourcing of SBT, while helping prioritise future research in areas where robust translational evidence remains limited. Systematic review registration PROSPERO registration: CRD420251131906.
SN - 2046-4053
ER -